Winter 2015

Tag Archives: finance

Thesis: Obama’s regulations for the financial advisory industry will have little impact on advisor behavior.

President Obama last month said in a speech to members of the AARP (American Association of Retired Persons) that he has given the Department of Labor the permission to change its rule and the definition of fiduciary under the Employee Retirement Income Security Act. This simple change of one word’s definition has people in the financial advisory industry worried. The reasons behind this proposed change are obvious, to require the financial advisor to act in the best interest of their clients and disclose any and all fees associated with all potential investments ahead of time. Obama and his supporters argue here that the reasons for this this proposed rule changes are “that consumers are entitled to unbiased information, and that commission-based compensation structures generate inherent conflicts of interest.” The opposition argue that these changes will cause advice to “become more expensive or not available at all for small accounts or individual plan participants.” I am going to argue that these proposed changes will have almost no impact on advisor behavior.

I make my assertion that these changes will have little to no impact on advisor behavior because I am assuming that clients are going to be acting in the best interest of themselves and their own well being. If these clients are acting in their own best interests, then over time advisors who are charging higher fees for not acting in the best interest of the client will be weeded out. This is because if two advisors are identical and offer the same investment advice, but one, acting in the best interest of the client, invests their client’s money in a lower fee mutual fund, while the other advisor, not acting in the best interest of their client, invests the money into an equal mutual fund but one that charges higher fees for themselves, the returns for advisor #2 will be lower after all fees. This lower return will, over time, cause clients to switch advisors and go to the one who is acting in the best interest of their clients. They will do this whether or not they even realize if their current advisor is acting in their best interest because the returns will, on average, be lower for financial advisors not acting in their clients best interests. This process will act as a filter in and of itself to remove financial advisors who aren’t acting in the best interest of their clients. Over time, as people realize they are not getting the most out of this relationship, they will move their money to advisors with higher returns who already act in the best interest of their clients.

Even though as Jason Zweig writes in his article, “Mary Jo White, chairman of the SEC, voiced her view that stockbrokers, insurance agents, and other financial salespeople should have to put their clients’ interests ahead of their own” making any changes to the wording of the rules in place will not significantly impact on financial advisor behavior.

Malkiel’s “Random Walk down Wall Street” offers very practical advice for household investors, but is dangerously misleading on the risks of long term investing.

The book starts out with a behavioral bent, pointing out all the times in which markets have gone crazy. I personally found the coverage of how simple name changes during the dot com bubble would cause certain stocks to zoom higher in value — a smoking gun for irrationality. Yet in spite of this behavioral bent, Malkiel is very down to earth about how many opportunities are available for people to beat the market. In the end of the first part of the book, Malkiel notes:

Markets are not always or even usually correct. But NO ONE PERSON OR INSTITUTION CONSISTENTLY KNOWS MORE THAN THE MARKET.

But even if people can’t beat the market, that doesn’t mean that there aren’t a lot of ways to underperform dramatically. I view his chapters on diversification in this light. He does a good job of introducing what can be very difficult mean-variance theory. Instead of using matrix algebra, he goes through an toy example of umbrella manufacturers and a resort owner and shows how it can be valuable to spread a nest egg across investments that, as a collective portfolio, can perform well come rain or shine.

When it comes to implementing investment advice, I also wholeheartedly agree with his argument for sticking with indexed funds. I enjoyed his statistical treatment of why reported mutual fund returns over-predict the actual investment opportunities available to investors due to survivorship bias. And whenever he brought up market “anomalies” such as the January effect or waiting for low price to earnings ratios to get higher returns, he was sure to note the uncertainty behind these signals, and to push people towards a passive investment strategy.

However, while I agree with the general message that households should be investing more into the stock market, both domestic and international, I think Malkiel substantially understates the true risks of investing in the stock market. In particular, he engages in the fallacy of time diversification when he tries to convince the reader that stocks are safer in the long run. The core of his argument centers around this chart:

Based on this chart, he argues that “A substantial amount (but not all) of the risk of common-stock investment can be eliminated by adopting a program of long-term ownership and sticking to it through thick and thin (the buy-and-hold strategy discussed in earlier chapters).”

But this relies on an empty notion of risk. The risk that is relevant for retirement investors is not the risk that their investment earns an average return above some other investment, for example long term bonds, but rather whether, at retirement, there is enough wealth left over to carry them through their golden years. As such, it’s not the average return that matters, but rather the total return over an entire working life!

And when it comes to this, the longer your investment horizon the larger the variance of the total return! If returns are independent over time, variance scales linearly. While there may be some mean reversion in the long run, as Malkiel notes in his discussion on PE ratios, this mean reversion can be very slow and doesn’t change the thrust of the analysis.

The risk from stock investment might be better visualized by thinking about what are the range of possible outcomes after 40 years in the stock market. Suppose each year stocks return 8% on average with a standard deviation of 20%, and that returns are independent (adding plausible levels of dependence does quantitatively little to the results). Suppose further that the investor’s utility is log, so that negative outcomes hurt a lot and extremely positive events aren’t that positive. Then the potential life paths for utility are summarized in the chart below. Each black line represents one potential history of an investor going 40 years in the stock market.

From this diagram it’s clear that risk rises over time. Sure, you have a tendency to drift up, but the bad outcomes get very bad. So even if the variance of the average return goes down, the variance of that average return multiplied by the investment timescale keeps on going up.

The gap between market forecasts of inflation and where inflation will likely go may be a feature, not a bug. This gap is a risk premia that can be informative about what scenarios are worrisome to investors, and as such may be useful for policy makers deciding on how to weight the relative costs of inflation and deflation.

Justin Wolfers’ recent recent NYT article on inflation expectations sets the stage. In this article, he walks through an academic asset pricing paper that estimates a probability distribution for future inflation based on the prices of bets on inflation. The basic idea is that there is a betting market in which people can place bets on where they think inflation will be going. Just like how a bookie’s prices say something about the probability of certain horses winning a race, the prices on this betting market (otherwise known as a derivatives market) make statements about the probability inflation ends up in certain zones. Justin summarizes the findings:

While traders view inflation of roughly 2 percent as the most likely outcome, the market is also telling us the probability of other levels of inflation — or deflation. And it is saying that the risks of missing the 2 percent target are extremely unbalanced: It is twice as likely that inflation will come in below the Fed’s target as above it.

But there’s another aspect to asset prices that isn’t as important for horse races: risk premia. Whether inflation is high or not is related to the strength of the jobs market and the economy as a whole. In particular, if I were to tell you that there was going to be deflation in two years, your best prediction would be that we were going through a double dip recession in which aggregate demand fell. This is clearly bad, and as such you would be willing to buy insurance against this scenario. In the language of horse betting, you would be willing to pay better than fair odds that there will be deflation. Sure you might lose money on average, but when deflation hits and you lose your job, at least you got your racetrack winnings to cushion the blow.

As such, the market forecast is equal to the true future expected inflation plus a risk premium that reflects whether low inflation or high inflation scenarios are scarier. If people are scared of a Japan style deflation, then the market forecast will underestimate true inflation. If on the other hand people are worried about 1970’s style stagflation, the market forecast will overestimate true inflation.

While this can be a nuisance if you want to get the “best” physical forecast of actual inflation, it can actually be tremendously valuable for policy makers who need to decide on whether to be more worried about the costs of high inflation or low inflation scenarios. Sure, if you’re playing a game and trying to minimize your prediction error the market forecast might not be helpful. But this can be very useful for policy! Negative risk premia on inflation expectations tell policy makers that low inflation scenarios are much worse than high inflation scenarios. If this is the case, then the inflation target has reason to be asymmetric — better to avoid scary deflation than deal with temporarily higher inflation.

As a more general point, this risk premia analysis shows how asset pricing is in some ways a form of quantitative psychology. Estimating risk premia can be interpreted as answering the question “based on these asset returns, what does that say about the kind of events that scare people”? And once policy makers know about these feared scenarios, they can adjust policy to make sure they do not come to be.

Much of the below discussion draws from the chapter on Dynamic Portfolio Choice from Andrew Ang’s Asset Management — a book I highly recommend

Comparing the return performance of rebalanced and “buy-and-hold” portfolios says little about the economic value of one strategy or the other. In a recent blog post, Corey Hoffstein shows that returns to rebalanced portfolios underperform in times of trends, and as such finds the evidence in favor of rebalancing to be quite mixed. But because there is no explanation of why rebalancing makes sense and how it creates value, return data tells relatively little about whether you should rebalance or not.

First let’s set the stage. Suppose you’re a long term investor with a million dollars and a time horizon of 25 years. And suppose that in this world the distribution of returns is assumed to be the same in each period, (iid), that you can trade once every year, and that you do not have access to any “inside tips” that would tell you any information about the distribution of stock returns. The first assumption is reasonable because if everybody knew returns were going to be high tomorrow, they would just buy today. The second is just for simplification, and the third one reflects the situation of most individual investors without access to any kind of special research team (not that institutional investors have access to the secret sauce either)

In this world, there are two broad classes of trading strategies: static and dynamic. A static strategy just buys and holds. Set up your 60/40 stocks/bonds portfolio and wake up 25 years later, collecting whatever capital gains you get. A dynamic strategy changes how much to buy and sell in each period depending on your wealth. Rebalancing refers to the dynamic strategy of starting out at a certain portfolio allocation, say 60 percent stocks and 40 percent bonds, and in each period selling or buying to go back to this allocation. So if stocks do really well one year while bonds do poorly (say in 2013), then sell some stocks and buy more bonds.

Apriori, it would be strange if a dynamic trading strategy were dominated by static trading strategy. Under the conditions I described above, rebalancing does dominate because it allows you to reset your risk exposure every period.

To see why, change the perspective from thinking about the trades you’re doing and instead think about the decision to change your risk exposure over time. Start from the assumption that your risk aversion does not change over time. If you fail to rebalance, as the share of stocks in your portfolio increases over time, you are choosing to increase your overall exposure to your stock market. But wait! If if it’s optimal for you to hold that riskier balance in the second year, then you should have held that in the first year! Expected returns haven’t changed, nor have your preferences. So don’t let the name of “buy and hold” fool you. Just because you’re not trading under a buy-and-hold strategy, you are making an active choice about your risk exposures.

But why does rebalancing create value? The market in aggregate cannot rebalance —if you’re selling stocks to rebalance, somebody has to be buying them from you. If you’re earning a rebalancing premium, there has to be some reason why others are willing to pay you.

Here is a point that Corey does hit on — rebalancing doesn’t work if prices are trending upwards over a long period of time. Another way of putting it is that if the distribution of returns changes over time, a strategy of rebalancing will have you buying more into stocks that may be worth nothing one day. In other words, rebalancing is a strategy that is short regime changes. Rebalancing works great if tomorrow’s returns look like today’s. It’s a horrible idea if, like in 1990’s Japan, stocks collapse and don’t come back even after 20 years.

And here’s why there is a long run rebalancing premium — you’re protecting others from extreme changes in the market environment. So rebalancing is good for keeping risk exposures on time, but at the risk of black swan events that permanently change the landscape of returns.

If I knew for certain that the German 10 year bond would trade at a 3% yield in a year, I would be fantastically bullish on Eurozone stocks. Imagine what that world would look like. Because long term bond yields are driven a large amount by inflation expectations, a 3% yield would suggest that inflation is returning to the Eurozone. Aggregate demand would be restored, a European “lost decade” averted.

In short, an unconditional forecast of high long term bond yields should be paired with a conditional forecast of economic strength. This connection between joint forecasts of long term bond yields and economic conditions allows me to apply the theory of risk neutral pricing, and explain why

Term premiums should be in a secular decline

How a temporary oil shock can have such an effect on long term bond yields

In the canonical theory of asset pricing, current prices should be the discounted value of expected future scenarios under the risk neutral measure (See chapter 1 of “Asset Pricing”, for example). What this concretely means is that payoffs in future states that “hurt” a lot get weighted more relative to their true physical probability, and that scenarios that hurt less are downweighted.

What does it mean to “hurt”? The classic theory is based off of consumption pricing. If the economy is doing poorly, then marginal utilities are high, and therefore any payoffs in these states of the world have magnified effects on utility. If assets do well in these states of the world, they should earn less return because they insure people against the worst in these bad states of the world.

But fund managers set prices, you might say, and they certainly don’t rely on their performance fees for consumption. But even though fund managers don’t “consume” out of their returns, it should be clear that their levered positions, as an aggregate, perform better when the global economy is strong. And if things go too poorly, margin calls and other liquidity stresses can be very costly. Hence fund managers too should be expected to worry more about how assets pay off in bad economic times.

In this model, a risk premium for long term bonds arises when the painful economic scenarios are also scenarios in which interest rates are high. This can happen, for example, if the central bank loses control of inflation and causes interest rates to skyrocket, as in the 1970’s in the United States.

But as the thought experiment at the beginning of this post reminds us, these high interest rate states of the world are looking less painful relative to low interest rate states of the world. High rates mean things are getting back to normal. Low rates mean continued stagnation.

Concretely, this is a reason for a secular decline in long term bond yields. Term premia have fallen because these bonds are even more negatively correlated with bad economic outcomes.

On a closing note, how does this risk neutral pricing explanation interact with the oil price shock? One explanation for the global fall in bond yields is the global fall in oil prices. Lower oil prices, hence lower inflation expectations and hence lower long term bond yields.

I cannot reject this explanation. But the magnitudes don’t seem to make enough sense. If we attribute the 60 basis point drop in the 10 year breakeven since June to oil prices, that implies the 10 year price level is forecasted to be 12 percent lower than what people thought in June.

The value of the risk neutral pricing story is that it can explain why a temporary change in the oil price can have an outsize effect on the 10 year bond yield. If a glut of oil rules out negative supply shocks that drive inflation and long term bond yields higher, then that strengthens the claim that high long term bond yields will be associated with stronger economic conditions. As such factors affecting oil prices today can have large effects on the yield curve.

After the European central bank announced new bond purchases, bond prices for all major European sovereigns rose. This does not seem surprising. Fixed supply of bonds, central bank increases demand, it’s natural for prices to rise. However, if bond yields do not rise soon that would be bad news for the ECB’s goal of getting back to 2% inflation.

The U.S. experience with QE I and QE II were associated with higher bond yields. This is clear from the plot below produced by Michael Darda, chief market strategist at MKM partners.

Changes in US inflation expectations can explain the changes in the first two QE periods. Recall the long term nominal bond yield decomposition into expected future real interest rates, a term premium, and inflation expectations. Suppose we believe that real interest rates and the term premium are pinned down by productivity and preferences, and are therefore invariant to monetary policy. Then it must be that the reason the yields rose was because inflation expectations rose. Indeed, this is what inflation expectations as proxied by the 10 year TIPS breakeven suggest.

In my view, this is one of the most convincing arguments that QE “worked” in the US — the market very much believed that the asset purchases would drive up the price level. Therefore if bond yields in Europe don’t show any increase, that means the market does not expect the ECB to be successful in its crusade to raise inflation.

One might argue that this argument misses out on the liquidity effect — i.e. the fact that monetary expansions have short run effects on bond yields. Central bank cash translates into higher bids for bonds, and since there are now fewer bonds to go around, this pushes up the price. Indeed, we saw the inverse of this phenomenon during the “taper tantrum” two summers ago. After Bernanke announced the tapering off of bond purchases during the middle of the QE 3 period, 10 year bond yields had a dramatic 70 basis points rise from around 200 basis points to over 270. Contractionary policy clearly cannot raise inflation expectations, and so it’s clear that the rise in bond yields was the result of a liquidity effect.

Another argument to support the liquidity effect is that stock prices in Europe have also been rising. If the fall in bond yields reflect falling inflation expectations, that would have been very bearish for equities. The stock market rally thus contradicts the inflation expectations story.

However, the liquidity effect is a short run phenomenon. After smoothing out the market microstructure, in the end long term bond yields should still be determined by inflation expectations, expected real rates, and a term premium. So to see if the ECB’s purchases are having an effect, keep an eye out on long term bond yields and hope they go up.

Global bond yields are collapsing. Bond yields in almost every major economy — developed and emerging—are lower than they were 10 years ago. Bond yields in Greece have risen about 2 percentage points, but that’s because they’re having their own problems with staying in the Euro.

Collapsing bond yields have also flattened out the yield curve in the US, Germany, Japan, and the UK. These numbers are incredible. People arepaying the German government 3 basis points a year for a stretch of 5 years just for the government to hold their money! In Japan, the government is getting away with paying 0.2% for a 10 year bond.

Why might this be the case? There’s a few stylized facts to keep in mind.

This collapse is global.

Yield curves are flattening. Any story must have factors that can affect yields all the way 10 years out.

Based on these two facts, what can we rule out?

The reason for collapsing bond yields can’t just be relative currency appreciations. Uncovered interest rate parity predicts that countries with low bond yields have such low yields because the market forecasts that their currencies will appreciate. But this can’t be the case if everybody has much lower bond yields — there’s no currency to appreciate against.

Is it just oil? That’s certainly what a lot of the media thinks. I can’t rule it out. But if the driving story is oil, it must be that we expect oil prices to be continually falling over the course of the next 10 years. Low but stable oil prices aren’t enough. That would make the price level low now, but that wouldn’t generate a persistent downward pressure on the price level, i.e. disinflation. And given that oil is now as cheap as it was in 2003, this story seems implausible.

I want to entertain one more story — that the term premium is turning negative. The 10 year bond yield can be decomposed into three components: the real risk free 10 year yield, inflation expectations, and then a 10 year term premium that compensates people for holding longer term bonds. Research from the NY Fed finds that this term premium has been falling ever since the 1980’s. Why might this be?

One story that would explain this is based on the notion of risk neutral probabilities. In the canonical theory of asset pricing, current prices should be the discounted value of expected future scenarios under the risk neutral measure. What this concretely means is that future scenarios that “hurt” a lot in terms of lost consumption get weighted higher than their true physical probability, and that scenarios that hurt less are downweighted.

In normal times, it’s high interest rates that are bad times. High interest rates are times when the central bank tightens too much and pushes the economy into a demand side recession. But it’s not clear that’s the case any more. Think about Japan as an extreme example. The most plausible scenario in which Japanese bond yields rise is if the Japanese central bank manages to achieve its 2% inflation target. That would be incredible! It would make their debt burden so much more manageable and would definitely not be a “painful” state of the world.

This reweighting of probabilities translates into a negative term premium. Because risk neutral pricing means that you underweight the higher bond yield scenarios, bond yields will look “too low” if you compare them with the likely evolution of short rates.

Observe that this scenario can be global and highly persistent—satisfying the two stylized facts above. If there’s a global lack of aggregate demand, high inflation (and therefore high long term bond yield) states of the world are painless. Risk neutral pricing then means that the high interest rates states of the world should be discounted everywhere. These effects can also be highly persistent because they’re statements about monetary policy regimes.

Demand side factors are certainly playing a role. James Hamilton from Econbrowser estimates that dollar strength, global macro weakness as proxied for by copper prices, and the decline in 10 year rates explains around 44% of the fall in crude prices since July.

That leaves around half of the decline unexplained. By definition, if it’s not coming from the demand side it must be from demand. Many analysts have talked about fracking and the growth in tight oil in the United States as a major factor. But there’s two reasons to be skeptical.

First, increasing tight oil production has been a long time coming. That should have easily been priced in.

Second, more sober analyses of the expansion in US oil production that suggest that much of the hype surrounding US oil production substantially changing global prices is overrated. There’s just not enough oil of the right blends to be making such a huge impact on global markets.

In my view, any plausible story for the recent decline in oil prices has to explain why recent small shocks about the future state of the world can translate into such dramatic price moves today.

One possibility comes from a story about the OPEC put. OPEC’s announcement in November wasn’t just about not cutting production, but rather it represented a regime change about how OPEC would respond to lower prices. One way to think about it is that OPEC’s previous policy of cutting production at low prices functioned as a put option on oil. No matter what, there would be a price floor.

But now that put option is out of the window. Without it, the left tail in oil prices exerts an effect on the current price. This can happen in at least two ways. As a first order effect, people with oil stocks sell at expected value, and when the low price events become possibilities, you sell at a lower price. But there’s also an effect on storage. By removing the put option, OPEC raises the specter of highly volatile and potentially very low oil prices in all future periods. This makes oil much less worthwhile to store, and as such producers will flood the current market with their stocks.

The formalism resembles a Hotelling model in which speculators store oil only if the expected return is competitive with other market interest rates + a risk premium. Given that rates are so low, variance in the risk premium matters more. If we think that the states of the world with extremely low oil prices are “expensive risk” states of the world (because macro conditions are bad), then these risks should now play a powerful role in inducing drawdowns in oil stocks.